Study of Land Morphological Characteristics based on Digital Elevation Model (DEM) Data Derivatives from Unmanned Aerial Vehicles (UAVs) in Landslide-Prone Residential Areas

Abstract

This study aims to analyze the landform characteristics in the Tiban Koperasi residential area, Batam City, which is prone to landslides, using a Digital Terrain Model (DTM) derived from an Unmanned Aerial Vehicle (UAV). The study employs UAV photogrammetry with Ground Control Points (GCPs) and Independent Control Points (ICP) using static GNSS to improve the geometric precision of the data. Data processing was performed using photogrammetry software to generate orthophotos, a Digital Surface Model (DSM), and a Digital Terrain Model (DTM), while spatial analysis was conducted using GIS software through DTM -derived parameters such as slope, aspect, curvature, hillshade, flow direction, contour, and viewshed. The research results indicate that the data exhibit a high level of accuracy, as the georeferencing process using 5 GCP points yielded an XY error of 2.67 cm and a Z error of 0.42 cm. Geometric accuracy testing also confirmed that the data meet the RBI map accuracy standards for a 1:2,500 scale, Class 2, as per BIG Regulation No. 6 of 2018. Morphological analysis indicates that the elevation of the area ranges from 22 –62 m, with flat slopes (0 –8˚) dominating at 41.7%, the dominant slope direction is toward the northwest, and the dominant flow direction is toward the northeast at 25.66%. Curvature analysis indicates the presence of convex areas with potential for erosion and concave areas with potential to become zones of water accumulation. Overall, the study’s findings indicate that high -resolution UAV data and DTM -derived analyses can provide accurate land morphology information to support the identification of landslide risks, disaster mitigation, and the planning of safer residential areas